• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.401-408
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• 2000

In this paper, we proposed a fuzzy controller that founded by the general feedback control with the new adjustment method when it's tuning. The general feedback controller is operated that supply to the plant making the control input multiplying the appropriate gain of controller on the error between the output of the plant and the reference, But proposed feedback fuzzy controller consist of three loops. The inner loop consists of plant and an ordinary feedback controller. The fuzzy inference of controller performed by the outer loops, which is composed of a fuzzy modeling and inference. We can observe that the output of control system converges toward the reference. Also, the behaviour of feedback fuzzy system is converged from the transient. That is, we verified that designed fuzzy controllers was adapted effectively through the experiments in the hydraulic motor system using floating point DSP processor.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.56-62
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• 2012

This paper presents design and implementation of the speed controller for DC motor system using Embeded Target for TI C2000 DSP library in Matlab/Simulink is introduced. Speed controller are easily design and implemented by using the Matlab/Simulink program. Feedback of motor speed is processed through eZdsp F2812 AID converter using encoder and pulse meter as speed sensor. Real-time program of controller is drawn using Simulink and converted program code for speed control of P control, PID control and parameter estimation base adaptive control is downloaded into the TI eZdsp 2812 board. Experiments were carried out to examine validity of speed response for implemented controllers. And even if controlled plant becomes alteration studied controller design and implementation easily method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.141-144
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• 2001

In this paper, we proposed a neural network controller with a fuzzy compensator which compensate a output of neural network controller. Even if learn by neural network controller, it can occur a bad results from disturbance or load variations. So in order to adjust above case. we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning an inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. In order to confirm a performance of the proposed controller, we implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.233-237
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• 2012

In this paper, We propose a control system which compensate a output of a main Neual Network using a RTDNN(Recurrent Time Delayed Neural Network) with a FLC(Fuzzy Logic Controller)After a learn of main neural network, it can occur a Over shoot or Under shoot from a disturbance or a load variations. In order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. We can confirm good response characteristics of proposed neural network controller by the results of simulation.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.276-279
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• 2003

본 논문에서는 블루투스 장비 간 암호화를 위해 사용되는 암호화 모듈의 설계 및 구현에 관한 내용을 다룬다. 암호화 모듈은 기저 대역내에 암호화 키 생성 모듈과 암호화 엔진 모듈로 구성된다. 암호화 키 생성 모듈은 Cylink사에서 제안한 공개 도메인인 SAFER+(Secure And Fast Encryption Routine) 알고리즘을 사용하여 128bit 키를 생성한다. 그 구성은 키 치환을 위한 치환 함수(key-controlled substitution)와 선형 변환을 위한 PHT(Pseudo-Hadamard Transform)와 Armenian Shuffle 변환기로 구성된다. 암호화 엔진 모듈은 전송 패킷내의 페이로드 데이터와 생성된 사이퍼 키 스트림 데이터와 XOR연산을 통하려 암호화를 행하며 그 구성은 LFSR (Linear Feedback Shift Register)와 합 결합기로 구성된다. 이 중 암호화 키 생성 모듈은 LM(Link Manager)의 PDU(Protocol Data Unit) 패킷을 통해 상호 정보가 교환되므로 암호화키를 생성하는데 있어 시간적 제약이 덜 하다. 따라서 본 논문에서는 변형된 SAFER+ 알고리즘 구현하는데 있어 치환 함수의 덧셈과 XOR, 로그, 지수연산을 바이트 단위의 순차 계산을 수행함으로써 소요되는 하드웨어 용량을 줄이도록 설계하였다. 본 논문에서 제시한 모듈은 블루투스 표준안 버전 1.1에 근거하여 구현하였으며 시뮬레이션 및 테스트는 Xilinx FPGA를 이용하여 검증하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.42-48
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• 2002

The case that cannot show the satisfactory control results with a modeling error and a shortage of related knowledge about a plant is if a fuzzy controller designed based on the plant model or the experience applies to an actual plant. We must adjust the scale factor which is a controller again in order to improve control performance in case of this and needs a lot of time and costs because this regulation process is carried out with a trial and error way We proposes the fuzzy controller that an automatic control adjust scale factors according to fuzzy logic and normalizer in this paper We confirmed that an automatic adjusted fuzzy controller displayed good performance than the fuzzy controller that scale factors was fixed through simulation. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.54-60
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• 2002

In this paper, we proposed a hybrid neural network-fuzzy controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of loaming a inverse model neural network of Plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed speed controller get a good response compare with a neural network controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.160-168
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• 2000

In this paper, we study how the remote controllable mobile robot which could come to many via points with FLC(Fuzzy Logic Control) efficiently. The fabricated robot stop after the movement of single path method by four kinds of commands (forward, backward, turn left, turn right). To reduce disadvantages of this driving type, this paper reduce via points to goal position base on map which get from senor, let robot drive via point to via point on optimized path. An algorithm for the avoidance of unexpected obstacles by FLC is developed. And these algorithms are confirmed by computer simulations

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.155-162
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• 2023

This study analyzed the impact of negative information on co-branding, targeting co-branding consisting of a symbolic brand and a functional brand with similar brand assets. Through attribution theory, when consumers are exposed to negative information, they will infer the cause of the negative information. As a result, it was confirmed that when co-branding with a symmetrical symbolic brand and a functional brand, negative information has different effects on co-branding depending on the type. Negative information about the quality of co-branded products had a more negative impact on consumer attitudes than negative information about the iconic brand. It was confirmed that negative information about functional brands has a smaller impact than negative information about co-branding, but has a greater impact than negative information about symbolic brands. In addition, it was confirmed that negative information about the symbolic brand had a smaller negative impact on co-branding than negative information about the quality or functionality of the co-branded product.